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001 978-3-030-03730-7
003 DE-He213
005 20220801214424.0
007 cr nn 008mamaa
008 190218s2019 sz | s |||| 0|eng d
020 _a9783030037307
_9978-3-030-03730-7
024 7 _a10.1007/978-3-030-03730-7
_2doi
050 4 _aTK7867-7867.5
072 7 _aTJFC
_2bicssc
072 7 _aTEC008010
_2bisacsh
072 7 _aTJFC
_2thema
082 0 4 _a621.3815
_223
245 1 0 _aStochastic Computing: Techniques and Applications
_h[electronic resource] /
_cedited by Warren J. Gross, Vincent C. Gaudet.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXVI, 215 p. 133 illus., 34 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aForeword: Gulak -- 1. Introduction to Stochastic Computing (Gaudet, Gross, Smith) -- 2. Origins of Stochastic Computing (Gaines) -- 3. Tutorial on Stochastic Computing (Winstead) -- 4. Accuracy and Correlation in Stochastic Computing (Alaghi, Ting, Lee, Hayes) -- 5. Synthesis of Polynomial Functions (Riedel, Qian) -- 6. Deterministic Approaches to Bitstream Computing (Riedel) -- 7. Generating Stochastic Bitstreams (Hsiao, Anderson, Hara-Azumi) -- 8. RRAM Solutions for Stochastic Computing (Knag, Gaba, Lu, Zhang) -- 9 Spintronic Solutions for Stochastic Computing (Jia, Wang, Huang, Zhang, Yang, Qu, et al.) -- 10. Brain-inspired computing (Onizawa, Gross, Hanyu) -- 11. Stochastic Decoding of Error-Correcting Codes (Leduc-Primeau, Hemati, Gaudet, Gross).
520 _aThis book covers the history and recent developments of stochastic computing. Stochastic computing (SC) was first introduced in the 1960s for logic circuit design, but its origin can be traced back to von Neumann's work on probabilistic logic. In SC, real numbers are encoded by random binary bit streams, and information is carried on the statistics of the binary streams. SC offers advantages such as hardware simplicity and fault tolerance. Its promise in data processing has been shown in applications including neural computation, decoding of error-correcting codes, image processing, spectral transforms and reliability analysis. There are three main parts to this book. The first part, comprising Chapters 1 and 2, provides a history of the technical developments in stochastic computing and a tutorial overview of the field for both novice and seasoned stochastic computing researchers. In the second part, comprising Chapters 3 to 8, we review both well-established and emerging design approaches for stochastic computing systems, with a focus on accuracy, correlation, sequence generation, and synthesis. The last part, comprising Chapters 9 and 10, provides insights into applications in machine learning and error-control coding.
650 0 _aElectronic circuits.
_919581
650 0 _aLogic design.
_93686
650 0 _aProbabilities.
_94604
650 1 4 _aElectronic Circuits and Systems.
_938269
650 2 4 _aLogic Design.
_93686
650 2 4 _aProbability Theory.
_917950
700 1 _aGross, Warren J.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_938270
700 1 _aGaudet, Vincent C.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_938271
710 2 _aSpringerLink (Online service)
_938272
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030037291
776 0 8 _iPrinted edition:
_z9783030037314
856 4 0 _uhttps://doi.org/10.1007/978-3-030-03730-7
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c76328
_d76328